Train – fermatresearch/sdxl-weighting-prompts:66175a29

fermatresearch / sdxl-weighting-prompts

SDXL with prompt weighting available using Compel's syntax. Check the Github link for the docs.

Public
3.1K runs
A100 (80GB)
GitHub

Run with an API

Playground API Examples Train README Versions

If you haven’t yet trained a model on Replicate, we recommend you read one of the following guides.

Pricing

Trainings for this model run on Nvidia A100 (80GB) GPU hardware, which costs $0.0014 per second.

Create a training

Install the Python library:

pip install replicate

Then, run this to create a training with fermatresearch/sdxl-weighting-prompts:66175a29 as the base model:

import replicate

training = replicate.trainings.create(
  version="fermatresearch/sdxl-weighting-prompts:66175a2993706e1721076d5c7f92f0c81ec6d065ec20717527f05dd8528a1fc7",
  input={
    ...
  },
  destination=f"{username}/<destination-model-name>"
)

print(training)

curl -s -X POST \
-d '{"destination": "{username}/<destination-model-name>", "input": {...}}' \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  https://api.replicate.com/v1/models/fermatresearch/sdxl-weighting-prompts/versions/66175a2993706e1721076d5c7f92f0c81ec6d065ec20717527f05dd8528a1fc7/trainings

The API response will look like this:

{
  "id": "zz4ibbonubfz7carwiefibzgga",
  "version": "66175a2993706e1721076d5c7f92f0c81ec6d065ec20717527f05dd8528a1fc7",
  "status": "starting",
  "input": {
    "data": "..."
  },
  "output": null,
  "error": null,
  "logs": null,
  "started_at": null,
  "created_at": "2023-03-28T21:47:58.566434Z",
  "completed_at": null
}

Note that before you can create a training, you’ll need to create a model and use its name as the value for the destination field.